Exploring Spinvis; The Unconventional Sound of Erik de Jong
Spinvis (Erik de Jong) is a Dutch artist, who’s music is hard to categorize in a specific genre. Some even say that Spinvis is his own genre, but his music comes most close to the genres; experimental Lo-Fi, experimental pop, neo-psychedelia, alternative indie and even a bit of modern dance and electronics. The music is composed through sampling of different sounds, which vary from sound samples of computers and even sounds composed by differing attributes, such as pot lids, a whistle and a keyboard. The texts of the songs cohere with these sounds and are almost poetic and supported by the melancholic voice of Erik. The first album, “Spinvis (2002)”, can be characterised as the most alternative and makes mainly use of computer based sampling, attributes and sensational song texts. From his third album on, “Dagen van Gras, Dagen Van Stro (2005)”, he is accompanied by his band. The corpus that will be studied is a sample of different songs of Spinvis, which will be compared to a sample of different songs that are of coherent genres of Spinvis. The playlist ‘Spinvis project’ was made and consist of different songs of every album made by Spinvis. In addition, a second playlist ‘Spinvis project genre’ was made, consisting of a random selected sample of songs by coherent genres. Both the playlist will be analysed to try to distinguish what specific features of Spinvis can be heard and if these features can be found in the different genres playlist. I expect that many features of Spinvis can be found in many different coherent genre songs, since it is hard to assign Spinvis to one specific genre.
Can Spinvis songs be categorized to different genres?
spinvis_project |> # Start with awards.
mutate(
mode = ifelse(mode == 0, "Minor", "Major")
) |>
ggplot( # Set up the plot.
aes(
x = valence,
y = energy,
size = loudness,
colour = mode
)
) +
geom_point() + # Scatter plot.
geom_rug(linewidth = 0.1) + # Add 'fringes' to show data distribution.
geom_text( # Add text labels from above.
aes(
x = valence,
y = energy,
label = label
),
data =
tibble(
label = c("Spinvis", "Genre"),
category = c("Spinvis", "Genre"),
valence = c(0.104, 0.0339),
energy = c(0.992, 0.00166)
),
colour = "black", # Override colour (not mode here).
size = 3, # Override size (not loudness here).
hjust = "left", # Align left side of label with the point.
vjust = "center", # Align vertical center of label with the point.
nudge_x = 0.02 # Nudge the label slightly right.
) +
facet_wrap(~ category) + # Separate charts per playlist.
scale_x_continuous( # Fine-tune the x axis.
limits = c(0, 1),
breaks = c(0, 0.50, 1), # Use grid-lines for quadrants only.
minor_breaks = NULL # Remove 'minor' grid-lines.
) +
scale_y_continuous( # Fine-tune the y axis in the same way.
limits = c(0, 1),
breaks = c(0, 0.50, 1),
minor_breaks = NULL
) +
scale_colour_brewer( # Use the Color Brewer to choose a palette.
type = "qual", # Qualitative set.
palette = "Paired" # Name of the palette is 'Paired'.
) +
scale_size_continuous( # Fine-tune the sizes of each point.
trans = "exp", # Use an exp transformation to emphasise loud.
guide = "none" # Remove the legend for size.
) +
theme_light() + # Use a simpler theme.
labs( # Make the titles nice.
x = "Postiveness of the song",
y = "Energeticness of the song",
colour = "Mode"
)
The two playlist that are compared in both graphs are a Spinvis playlist, only containing songs of Spinvis (Category: Spinvis project) and a playlist with songs that are in overlapping genres with spinvis (Category: Spinvis project genre). Both graphs show the measured features and belonging values. The first plot shows a bargraph in which little differences can be found. The biggest difference can be seen between the categories and features of ‘Liveness’ and ‘Valence’. Meaning that the songs of Spinvis are less featuring liveness compared to overlapping genres, but are more featuring valence.
In addition a second graph was plotted. Given that the playlist of only spinvis songs is compared to a playlist of several songs that all are from different genres overlapping with spinvis. Meaning that it is interesting to look at also the means and how these fluctuate and show very different results. Both for spinvis as for the category genre, both have many outliers fluctuating eatheir down or up. For valence you can see that both the maximum as the minimum in both categories is the same but the mean is much different.
The B-side (Doris Day)
The song Doris Day, is originally from the Dutch pop group ‘Doe Maar’. Songs were characterized by a mixture of reggae, pop, ska and Dutch vocals and formed a unique style of nervous, puncky pop songs. The group formed the emergence of the genre “Nederpop”, a genre Spinvis is also associated with. In 2012 the collaboration album Versies/Limmen Tapes was released, which contained some of the best known songs of Doe Maar with a twist. [Doris Day - Rapversie](https://open.spotify.com/track/1yoS3M2rBgDVfWh807OTv5?si=be3f6ce902cc4215 is one of these songs, a collaboration between singer Sef, Spinvis and the group Doe Maar.
Can we capture the sound of Spinvis
*** Tot
ziens, Justine Keller In the context of the song “Tot Ziens, Justine
Keller” by Spinvis, the Cepstrogram provides insights into the spectral
characteristics of the audio signal over time. By visualizing the
cepstral coefficients, the Cepstrogram can reveal patterns and changes
in pitch, timbre, and other spectral features throughout the song.
Interpreting the Cepstrogram requires some understanding of signal processing and audio analysis techniques. Generally, areas of higher magnitude or intensity in the Cepstrogram may correspond to prominent features or changes in the audio signal, such as musical notes, vocal inflections, or instrumental passages. Applaus
Capturing Patterns; Spinvis and Genres
Timbre based Self-similarity Matrices: to see structure of the songs
The Key to Spinvis
The songs that are seen in the Chordograms are: Voor Ik Vergeet (Spinvis)
Hemel Valt (Typhoon)
Let It Happen (Tame Impala)
What can be seen is the song of Spinvis shows a less clear pattern, and spotify seems to think that the song have come to an end at 220 sec. Also spinvis sound is mostly in c# minor, Ab Major and Db Major. Typhoon has a very clear pattern in his song and is mostly in the keys F Major and F Minor Tame Impala has a less clear pattern, around 100 sec is a small decrease. Around 250 sec till 300 sec there is also a moment spotify is not sure how to analyse. In the song (starting from 3:50) there is a soundsequence that is probably hard to analyse for spotify, given the big yellow part. Furthermore it is hard to say in which specific key the song is played.
Tempo Tales of the Astronaut who learned to Breathe
*** A Fourier-based tempogram of the song Astronaut
is shown. An attempt to analyse the tempo of the song is made, by using
Spotify’s API. An estimation made by Spotify is a tempo of …. In some
freer-form sections of the piece, tempo estimation is almost
impossible.
To compare the the temporal features of the song, another Fourier-based tempogram was conducted of the song Breathe In, Breathe Out. Which shows that Spotify made an estimated tempo of ….
Can we cluster what we know?
The End of exploring Spinvis
Both the playlist will be analysed to try to distinguish what specific features of Spinvis can be heard and if these features can be found in the different genres playlist. I expect that many features of Spinvis can be found in many different coherent genre songs, since it is hard to assign Spinvis to one specific genre.
weaknesses of the corpus: A weakness of the corpus is that for the corpus, many different songs are examined strengths of the corpus: interesting results overview: discussion/conclusion:
…